When there is breaking news, or a major event in sports, entertainment, or politics, people will be using various forms of social media to discuss it live in real time. Frequently, these conversations over social media provide information that is available through no other form of media. Some events are discussed in social media conversations long before any more conventional reporting can catch up to them, and involve volumes of information beyond the capacity of conventional media to represent. It can thus be valuable to collect a stream of these social media messages, so that they can be visualized, data-mined, or simply shown in a unified stream. Usually, there will be no single, organized way to get all the messages. The conversations can take place over a wide array of platforms, from text-based messaging over social networks to online discussion boards, in multiple languages, and involve enormous numbers of participants. The sheer volume of communication passing over networks makes it highly challenging to find and collate conversation on a particular topic. Not only is there a vast amount of data to search for, the data is far from static. Traditional indexing-based searches cannot account for the burgeoning volume of new conversation streaming onto public platforms around the world when the conversation is taking place.
Therefore, there is a need for an effective way to locate and collect electronic conversations concerning a topic.